Application of particle filters to a map-matching algorithm

This paper presents a numerical probabilistic approach to the map-matching problem within the framework of the Bayesian theory. The proposed solution is based on the sequential Monte Carlo method—the so-called particle filtering. This algorithm can be adapted for implementation on real-time portable...

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Bibliographic Details
Published inGyroscopy and navigation (Online) Vol. 2; no. 4; pp. 285 - 292
Main Authors Davidson, P., Collin, J., Takala, J.
Format Journal Article
LanguageEnglish
Published Dordrecht SP MAIK Nauka/Interperiodica 01.10.2011
Subjects
Aerospace Technology and Astronautics
Engineering
Geophysics/Geodesy
Road Segment
Track Error
Particle Filter
Dead Reckoning
Road Link
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ISSN2075-1087
2075-1109
DOI10.1134/S2075108711040067

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Summary:This paper presents a numerical probabilistic approach to the map-matching problem within the framework of the Bayesian theory. The proposed solution is based on the sequential Monte Carlo method—the so-called particle filtering. This algorithm can be adapted for implementation on real-time portable car navigation systems equipped with GPS or dead reckoning sensors. The reliability and accuracy of this algorithm were investigated using simulated data and data from real-world driving tests in urban environments.
ISSN:2075-1087
2075-1109
DOI:10.1134/S2075108711040067